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Carlos A. Haro
Economist with experience in data science
Main focus on data visualization and supervised learning.
Education
(ITAM) Instituto Tecnológico Autónomo de México
B.S., Economics
Mexico City, Mexico
2014 - 2018
Experience
Sr. Data Scientist
Mexico’s Central Tax Administration Office
(Servicio de Administración Tributaria)
Mexico City
Jan. 2019 - present
- Development and deployment of a supervised model for classifying tax debt | R (tidyverse, ranger), Python (scikit-learn, pandas)
- Designed and taught three courses for the institution’s staff training: introduction to R, basics of exploratory data analysis, building data science pipelines using Makefiles | R (tidyverse, ggplot2), GNU Make
- Designed a pipeline for automatic generation of frequent data visualization reports | R Markdown (ggplot2, shiny)
- Perform network analysis to detect tax evasion communities | R (tidyverse, visnetwork, ggraph)
- Version control of cloropleth maps for the geographical display of taxpayer’s data | R (leaflet QGis)
Economic Analyst | Jr. Data Scientist
EnergeA (Energy Sector Consulting Firm)
Mexico City
2018
- Developed a statistical model for identifying anti-competitive practices between the mid-stream natural gas providers | R
- Neighboring gas station’s competition analysis for identifying price discrimination | R
- Scrapped 100+ PDFs for ownership analysis of Mexico’s natural gas industry. | R (stringr, rselenium)
Miscellaneous
Hackaton challenge winner
Annual BBVA Hackaton Challenge
N/A
2019
(Participated as part of a team of 3 people)
Organizer: BBVA Bank
Challenge: Update and insert operation of a 50 million observations dataset in under 10 minutes.
Result: 95%+ accuracy of update and insert achieved in 4 minutes | Pyspark on AWS for the algorithm, RMarkdown for the report
Hackaton participant
Annual Banamex Hackaton Challenge
N/A
2019
(Participated as part of a team of 2 people)
Organizer: Banamex Bank
Challenge: Create any platform for aiding small mexican businesses (< 75,000 usd/year cash flow) flourish.
Result: Created a live dashboard service that calculated the probability of succes of a business given
initial investment, number of employees, employee salary, etc. | R (shiny), Python (scikit-learn), AWS